IEEE Robotics & Automation Magazine - September 2018 - 84

referred to as dynamic when the dynamics of both the object
and the robot are essential to successful task execution.
A nonprehensile dynamic manipulation task can be generally described as a task where the object is subject only to unilateral constraints, and the dynamics of both the object and
the manipulating hand as well as the related kinematics and
the (quasi-)static forces play a crucial role. Pushing objects,
folding clothes, carrying items on a tray, cooking in a pan, and
performing some surgeries are examples of nonprehensile
manipulation tasks. From a robotic point of view, most nonprehensile manipulation systems are underactuated, raising
controllability challenges. However, dynamic nonprehensile
manipulation has several advantages, such as the increase in
available robot actions, bigger operative workspaces, and
enhanced dexterity in dynamic tasks.
Literature
The literature contains well-established grasping techniques
[1] and control methods for manipulation tasks with grasp
[2]. Within industrial applications, where simplicity and cost
are most relevant, grippers or special-purpose devices are
widely used. Nevertheless, the necessity for robots working
in anthropic environments is growing rapidly, as shown by
the European Strategic Research Agenda (eSRA) [23], which
states that robots will pervade a portion of the market in
domestic appliances, assisted living, entertainment, and education. Therefore, robots should not need specific tools for
each action, but they should exploit multipurpose devices,
such as multifingered hands, and they should rely on the
dexterity conferred by the designed control algorithms.
Manipulation dexterity is one of the main research challenges currently being addressed by the robotics community.
As explained previously, a nonprehensile manipulation task is
a dexterous task par excellence. Some tasks are intrinsically
prehensile, e.g., screwing on or unscrewing a bottle cap. Other
tasks can be tackled both in a prehensile or a nonprehensile
manner, such as the aforementioned example of moving an
object on a table. Some tasks are inherently nonprehensile, e.g.,
carrying a glass full of water on a plate. Other tasks are hybrid,
in the sense that, to reach the goal, both prehensile and nonprehensile actions are required, such as when a juggler has to
repetitively catch and throw balls in a cascade juggling pattern.
The literature, however, is not fully developed for nonprehensile manipulation tasks. The classic way to cope with
them is to split a task into simpler subtasks, referred to as
nonprehensile manipulation primitives [3], such as throwing
[4], dynamic catching [5], batting [6], juggling [7], dribbling
[8], pushing [9], sliding [10], rolling [11], and so on [27].
Each primitive, equipped with its own motion planner and
controller, is then turned on and off during a complex
manipulation task by a high-level supervisor [12]. Among
the mentioned nonprehensile manipulation primitives, only
rolling and batting are fully covered in the literature. There is
also a lack of a general unified theoretical framework in the
field, causing the continuous investigation of ad hoc motion
planners and controllers to individually solve the specific
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september 2018

tasks. The main reason may be found in the possible change
of the contact status during a nonprehensile manipulation
task, leading to nonsmooth dynamics of the entire system,
which complicates the control design. For this reason, dynamic nonprehensile manipulation may be considered the
most complex manipulation action, deserving attention as
requested by the eSRA, and posing many research challenges
to be solved.
The RoDyMan Project
In the described context, the RoDyMan project aims to develop a service robot able to manipulate elastic, soft objects, and
both rigid and nonrigid objects in a nonprehensile way; the
ambitious goal is to bridge the gap between robotic and
human task execution capability. To reach the planned goals,
three main research challenges have been identified:
● Mechatronic development and assembly: A mobile robotic
platform equipped with two commercial arms and multifingered hands are necessary to perform the dynamic
manipulation tasks planned for the project.
● Modeling and perception: Real-time requirements posed by
robot interaction with deformable objects during dynamic
nonprehensile manipulation actions are essential to fulfill
the required tasks.
● Control techniques for nonprehensile dynamic manipulation:
The goal of the project is to advance the state of the art in
controlling rigid objects in a nonprehensile way and to
begin investigating the problems relative to the prehensile
and nonprehensile manipulation control of deformable objects.
The final demonstrator of the project will be an autonomous pizza maker since preparing a pizza involves an extraordinary level of manual dexterity.
Other Approaches
Other projects have attempted to address nonprehensile
manipulation problems using different approaches. The
RIBA robot is able to lift patients up from and set them down
on their beds and/or wheelchairs [24]. The soft body of the
robot is designed to make the interaction with humans safe.
The transporting task performed is nonprehensile, but the
manipulation task is not dynamic because the patient's body
is considered a rigid object, and only motion-planning techniques for lifting the body up are investigated. The task is
very similar to a pick-and-place operation where the transporting motion is addressed in a nonprehensile fashion.
The ERC SHRINE project goals focus on enhancing robot
manipulation capabilities to overcome barriers preventing
robots from safe and smooth operations within anthropic
environments [25]. The objective of the RoDyMan, in some
cases also performed in a nonprehensile way, is to cooperate
with humans.
The results achieved so far within the RoDyMan project for
the aforementioned three research challenges are described in
the following, and videos of the related experiments can be
found on the PRISMA Lab YouTube channel [26].

IEEE Robotics & Automation Magazine - September 2018

Table of Contents for the Digital Edition of IEEE Robotics & Automation Magazine - September 2018